This application requests a Ruth Kirschstein National Research Service Award Individual Postdoctoral Fellowship for Dr. Pamela Newland to develop a program of research evaluating symptom clusters in multiple sclerosis (MS). MS is the most common disabling neurological disease often first identified in young and middle aged adults, affecting approximately 400,000 people in the United States alone. Research on symptom clusters in other diseases indicates clinical utility;but we do not know whether symptoms cluster or co-occur in persons with MS. The specific aims of this study include to 1): fully characterize symptoms experienced by patients with relapsing-remitting multiple sclerosis (RRMS), the most prevalent MS subtype;2) validate the revised symptom list generated (Aim 1) in patients with RRMS patients not involved with the focus groups, and 3): to determine, using cluster analysis, if there are symptom clusters in patients with RRMS and, if there are clusters, to examine the relationships between symptom clusters and RRMS course. Patients with RRMS of varying disease duration, age, and gender will be recruited to focus groups to identify and describe their symptoms from MS since diagnosis with an emphasis on co-occurring symptoms. Second, a cross-sectional study using a convenience sample of 220 patents with RRMS will validate the expanded symptom list and to determine the prevalence of individual symptoms and co-occurring symptoms. To identify symptom clusters, cluster analyses will be performed using two approaches, factor analysis and regression analyses (multiple regression and multiple logistic regression) to test for associations between symptom clusters and clinical outcomes. Understanding of symptom clusters and their likelihood of co-occurrence can assist nursing and other disciplines to prioritize care and anticipate needs. Identification and characterization of symptom clusters holds promise for future assessment and therapies for specific subgroups of persons with MS. PUBLIC HEALTH RELEVANCE: Multiple sclerosis (MS), a common neurological disease, leads to a multitude of symptoms, and health burden. This proposal provides new insight into the complexity of how symptoms occur and interact in MS that will be essential for future studies.